Time Series Data Analysis Method and Apparatus, Computing Device, and Storage Medium

Abstract

A time series data analysis method includes in response to a first analysis mode input by a user, analyzing first time series data by using a first time series analysis operator; updating the first time series analysis operator based on the first time series data and a first model parameter in the first time series analysis operator; and analyzing second time series data after the first time series data by using an updated first time series analysis operator.

1 . A method comprising:
 analyzing, in response to a first analysis mode input by a user, first time series data using a first time series analysis operator;   updating the first time series analysis operator based on the first time series data and a first model parameter in the first time series analysis operator to obtain an updated first time series analysis operator; and   analyzing second time series data using the updated first time series analysis operator,   wherein the second time series data is after the first time series data.   
     
     
         2 . The method of  claim 1 , wherein updating the first time series analysis operator comprises:
 determining a second model parameter based on the first time series data and the first model parameter; and   determining the updated first time series analysis operator based on the second model parameter.   
     
     
         3 . The method of  claim 2 , further comprising storing the second model parameter. 
     
     
         4 . The method of  claim 1 , further comprising training the first time series analysis operator based on third time series data, wherein the third time series data is before the first time series data. 
     
     
         5 . The method of  claim 4 , further comprising obtaining the first time series data, the second time series data, and the third time series data from a time series database. 
     
     
         6 . The method of  claim 1 , further comprising:
 training a second time series analysis operator based on the first time series data; and   analyzing, in response to a second analysis mode input by the user, the first time series data using the second time series analysis operator.   
     
     
         7 . An apparatus, comprising
 a memory configured to store instructions; and   one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to:
 analyze, in response to a first analysis mode input by a user, first time series data using a first time series analysis operator; 
 update the first time series analysis operator based on the first time series data and a first model parameter in the first time series analysis operator to obtain an updated first time series analysis operator; and 
 analyze second time series data using the updated first time series analysis operator, 
 wherein the second time series data is after the first time series data. 
   
     
     
         8 . The apparatus of  claim 7 , wherein when executed by the one or more processors, the instructions further cause the apparatus to:
 determine a second model parameter based on the first time series data and the first model parameter; and   determine the updated first time series analysis operator based on the second model parameter.   
     
     
         9 . The apparatus of  claim 8 , wherein when executed by the one or more processors, the instructions further cause the apparatus to store the second model parameter. 
     
     
         10 . The apparatus of  claim 7 , wherein when executed by the one or more processors, the instructions further cause the apparatus to train the first time series analysis operator based on third time series data, and wherein the third time series data is before the first time series data. 
     
     
         11 . The apparatus of  claim 10 , wherein when executed by the one or more processors, the instructions further cause the apparatus to obtain the first time series data, the second time series data, and the third time series data from a time series database. 
     
     
         12 . The apparatus of  claim 7 , wherein when executed by the one or more processors, the instructions further cause the apparatus to:
 train a second time series analysis operator based on the first time series data; and   analyze, in response to a second analysis mode input by the user, the first time series data using the second time series analysis operator.   
     
     
         13 . A computer program product comprising computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to:
 analyze, in response to a first analysis mode input by a user, first time series data by using a first time series analysis operator;   update the first time series analysis operator based on the first time series data and a first model parameter in the first time series analysis operator to obtain an updated first time series analysis operator; and   analyze second time series data using the updated first time series analysis operator,   wherein the second time series data is after the first time series data.   
     
     
         14 . The computer program product of  claim 13 , wherein when executed by the one or more processors, further cause the apparatus to:
 determine a second model parameter based on the first time series data and the first model parameter; and   determine the updated first time series analysis operator based on the second model parameter.   
     
     
         15 . The computer program product of  claim 14 , wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to store the second model parameter. 
     
     
         16 . The computer program product of  claim 13 , wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to train the first time series analysis operator based on third time series data, and wherein the third time series data is before the first time series data. 
     
     
         17 . The computer program product of  claim 16 , wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to obtain the first time series data, the second time series data, and the third time series data from a time series database. 
     
     
         18 . The computer program product of  claim 13 , wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to:
 train a second time series analysis operator based on the first time series data; and   analyze, in response to a second analysis mode input by the user, the first time series data using the second time series analysis operator.   
     
     
         19 . The computer program product of  claim 13 , wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to determine the first model parameter using a moving average algorithm. 
     
     
         20 . The computer program product of  claim 13 , wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to determine the first model parameter using an exponential moving average algorithm or a stochastic gradient descent (SGD) algorithm.